An algorithm for implementing a minimal stream X-Machine model to test the correctness of a system

Phung, Khoa; Ogunshile, Emmanuel

doi:10.1109/conisoft50191.2020.00023

Cited by 5 publications

(2 citation statements)

References 29 publications

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“…satisfies the following conditions: for every two states q 1 , q 2 ∈ Q, if (q 1 , q 2 ∈ d s ) then q 1 and q 2 are separated by W s . The relation d s identifies pairs of states that are known to be separated by W s , Based on Equation 3, in [43] and [44], we proposed T-SXM which is a modelling tool developed based on the concept of Stream X-Machine and state-counting approach for automatic test generation. The T-SXM tool has been used to model chronic diseases (e.g., Type II Diabetes) with promising results in [44] and [45].…”

Section: A Generate Test Cases For Jresmentioning

confidence: 99%

Error-Type—A Novel Set of Software Metrics for Software Fault Prediction

2023

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In software development, identifying software faults is an important task. The presence of faults not only reduces the quality of the software, but also increases the cost of development life cycle. Fault identification can be performed by analysing the characteristics of the buggy source codes from the past and predict the present ones based on the same characteristics using statistical or machine learning models. Many studies have been conducted to predict the fault proneness of software systems. However, most of them provide either inadequate or insufficient information and thus make the fault prediction task difficult. In this paper, we present a novel set of software metrics called Error-type software metrics, which provides prediction models with information about patterns of different types of Java runtime error. Particular, in this study, the ESM values consist of information of three common Java runtime errors which are Index Out Of Bounds Exception, Null Pointer Exception, and Class Cast Exception. Also, we proposed a methodology for modelling, extracting, and evaluating error patterns from software modules using Stream X-Machine (a formal modelling method) and machine learning techniques. The experimental results showed that the proposed Error-type software metrics could significantly improve the performances of machine learning models in fault-proneness prediction.

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Section: A Generate Test Cases For Jresmentioning

confidence: 99%

Error-Type—A Novel Set of Software Metrics for Software Fault Prediction

2023

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“…and test scenarios are built to be automated and replicated at any stage of software development. Such preparation increases the efficiency of the testing process [19], [54], [55]. • The enhancement of program design and architecture results from the close connection between the tested code and the test process itself.…”

Section: • Compatibility Of Tests With Automation -Individual Testsmentioning

confidence: 99%

Development of Automatic Source Code Evaluation Tests Using Grey-Box Methods: A Programming Education Case Study

Skalka,

Drlík

2023

IEEE Access

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Increasing the effectiveness of programming education has emerged as an important goal in teaching programming languages in the last decade. Automatic evaluation of the correctness of the student's source code saves teachers time and effort and allows a more comprehensive focus on the preparation of assignments with integrated feedback. The study aims to present an approach that will enable effective testing of students' source codes within object-oriented programming courses while minimising the demands on teachers when preparing the assignment. This approach also supports variability in testing and preventing student cheating. Based on the principles of different types of testing (black-box, white-box, grey-box), an integrated solution for source code verification was designed and verified. The basic idea is to use a reference class, which is assumed to be part of every assignment, as the correct solution. This reference class is compared to the student solution using the grey-box method. Due to their identical interface (created by assignment), comparing instance states and method outputs is a matter of basic programming language mechanisms. A significant advantage is that a random generation of test cases can be used in such a case, while the rules for their generation can be determined using simple formulas. The proposed procedure was implemented and gradually improved during 4 years on groups of bachelor students of applied informatics with a high level of acceptance.

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